@inproceedings{8e6edfaf728c495ba868fea821d3ae58,
title = "Blind deconvolution of natural images using segmentation based CMA",
abstract = "In this paper, we analyze the applicability of Constant Modulus Algorithm (CMA), one of the most widely used and tested blind equalization technique to blind image deconvolution. With a detailed mathematical analysis, we show that the strong correlation between the neighboring spatial locations found in natural images becomes a major constraint on the convergence of CMA. In order to overcome this constraint, we introduce a novel image pixel correlation model in relation with natural image statistics. Based on this model, a segmented blind image deconvolution through CMA is proposed. The robustness of the proposed algorithm with natural images is discussed in terms of efficiency and effectiveness.",
keywords = "Blind image deconvolution, Constant modulus algorithm, Equalization, Image correlation, Kurtosis, Meso-Kurtic, Natural image statistics, Stationary points, Whitening",
author = "Samarasinghe, {Pradeepa D.} and Kennedy, {Rodney A.}",
year = "2010",
doi = "10.1109/ICSPCS.2010.5709712",
language = "English",
isbn = "9781424479078",
series = "4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings",
booktitle = "4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings",
note = "4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 ; Conference date: 13-12-2010 Through 15-12-2010",
}